How to Create More Value From Employee Surveys

CEOs often proclaim that “people are our most important asset.” Yet many HR departments find themselves unable to play a significant part in translating these words into reality for several reasons:

• Some HR departments rely so heavily on benchmarking that they fail to customize their strategies to their organization’s unique circumstances, thereby almost guaranteeing they will, at best, stay average.

• Others get too caught up in the flavor-of-the-month programs.

• Many are so busy putting out fires they have no time to address what’s truly important — drivers of business results.

• Despite its potential, too often the only thing that comes out of the annual employee engagement survey is a big data dump with no real impact.

Analytics can ensure HR is not pigeonholed as non-strategic and out-of-touch. “It’s no longer possible for HR departments or functions to ignore analytics,” said Larry Costello, executive vice president, Tyco Fire and Security. “The forces bringing analytics to the forefront are simply too powerful to disregard.”

Talent leaders can use a four-step process to create an HR analytics strategy that will transform the traditional engagement survey into a source of actionable business intelligence.

Step 1 — Create a smarter employee survey. Traditional employee engagement or satisfaction surveys are not up to the task of producing actionable business intelligence. Engagement is necessary to produce great results, but it’s not sufficient. For example, in the Harvard Business Review article “Manage Your Human Sigma,” while describing an analysis of customer engagement at a multi-site retailer, Gallup researchers state, “Our working assumption was that at least a few of the top employee engagement stores would also be top customer engagement stores. We were wrong. Just one store appeared on both lists.”

There are two major deficiencies in most employee engagement surveys:

1. They pay too little attention to critical organization-level factors such as work processes, hiring processes and informal learning. These factors are big drivers of business results, but are typically not among the top employee engagement/satisfaction drivers. For this reason, they are under-measured in most surveys.

2. They miss the opportunity to tap into workforce wisdom about the drivers and impediments of what it takes for an organization to be a good seller and a good community and environmental steward — both of which are increasingly necessary to an organization’s ability to outperform its competition (Figure 1).

Employee survey content should be expanded to include a broader set of questions that go beyond HR’s current concept of employee engagement.

Step 2 — “Linkage analysis” to business outcomes. Next, statistically link the data from the smarter employee survey to data on desired outcomes. For example, Figure 2 shows the types of data that global technology company Applied Materials has statistically linked with its employee survey to create actionable intelligence for the business as a whole.

Linkage analysis can be done with soft outcomes data collected within a smarter employee survey, which includes engagement — including employees’ intent to stay and willingness to recommend the organization to friends as a good place to work — as well as elements such as employees’ reported ability to help the organization achieve its cost containment goals; and the extent to which employees report that the work environment supports excellent customer service.

Data on hard outcomes comes from outside the survey, such as sales, safety, turnover and customer satisfaction, and is then mapped to the survey. This involves aligning these outcomes to the survey responses of the employees who provided them. It is important to note that this mapping requires the survey be non-anonymous. Hence, creating business intelligence from a smarter employee engagement survey requires contracting with an independent third-party analytics firm, since failing to do so is likely to result in less-than-frank responses to a non-anonymous survey.

The specific statistical methodologies that should be used for the linkage analysis will depend on the outcome being analyzed. The techniques can range from complex multivariate analysis, such as logit regression or panel estimation techniques, for most individual-level data, to more straightforward univariate analysis — correlations and statistical testing of differences of means — for group data with small sample sizes.

However, it’s important not to get hung up on the statistical nuances since there are plenty of experts who can help with this. The critical point is that linkage analysis is the missing connection that allows organizations to move beyond guesswork, hope and intuition on the people side of their business.

“Leveraging analysis that connects areas like employee engagement to important business results is the missing link,” said Mary Humiston, senior vice president, global human resources, Applied Materials. “It is helping us to develop a strong fact-based HR strategy for driving improved business results. Identifying the unique human drivers of our business outcomes with precision and rigor is helping us to elevate our game.”

Step 3 — Create a rigorous, fact-based process to identify the best areas of opportunity. It’s important to understand that benchmarking is not analytics. For example, knowing that an organization benchmarks at the 90th percentile on a specific survey item should not be cause for celebration — unless linkage analysis reveals that the specific item drives an important business outcome. And a low score on a specific survey item should only create significant concern if it drives a key outcome. Benchmarking provides little, if any, basis for creating a fact-based HR strategy.

Figure 3, which is based on a confidential client case, illustrates this point. Each point in the graph represents a survey question.

The vertical axis shows how strong or weak the organization is on each survey item, measured relative to the overall organizational average. Survey items in the bottom half (Quadrants 3 and 4) are areas of weakness, while items in the top half (Quadrants 1 and 2) are strengths.

Following a survey, many organizations spend lots of time working on their lowest-scoring items. They would therefore focus heavily on seeking to improve survey item A — lower left corner — the item with the lowest overall score.

However, if a second piece of information is added to the mix, a different conclusion emerges. Take a look at the horizontal axis, which shows the results on how important each question is in predicting a key measure of sales success based on Step 2. Those items farther to the right (Quadrants 2 and 4) are positive predictors of sales success, and those items on the left (Quadrants 1 and 3) are negative predictors of sales. As expected, many more survey items are positive predictors than negative ones.

Remember survey item A with the lowest score? Turns out it’s a negative predictor of sales and therefore is actually a poor target for improvement. The best area of focus turns out to be survey item B, which has the fourth-lowest score, but is both an important positive predictor of sales and still an area of relative weakness. While it might be tempting to wonder what the specific survey questions are that correspond to A and B, that would miss the point, which is that each organization must do its analytics homework to determine the survey items that are most important for it rather than accept a one-size-fits-all answer.

The content of the actual survey items in this example doesn’t matter; the results will be different for every organization. That’s the point of doing this analysis — to help organizations move beyond benchmarking and target survey items that are the most important predictors of their organization’s business outcomes.

Step 4 — Make insightful and easy-to-understand recommendations. Getting to step 3 can be challenging, since it helps move organizations beyond potentially misleading one-size-fits-all benchmarking measures. But to enjoy the full advantage of this breakthrough, effectively communicating the findings from the analysis is essential. Three points to keep in mind:

1. Avoid data dumps and the temptation to share everything learned in the course of the analysis.

2. Home in on the most important findings and implications, and focus on those.

3. Communicate simply and compellingly. This is as much art as science, but it’s a critical skill to create actionable business intelligence on the people side of the business.

Figure 4 provides an example of how the insights from Step 3 can be presented in a way that makes it easy for senior executives to quickly absorb the most important findings.

The top areas of opportunity emerging from Step 3 provide a compelling business case to create a fact-based HR strategy to drive business results.

“At Applied Materials we are using analytics to convert both HR data and business data from information into actionable insights,” said Angela Sheffield, head of global workforce planning at Applied Materials. “The executive team is very engaged — they are asking for more. It really helps them to understand the link between what goes on in HR and our business results and guides them to where the biggest levers are for improvement.”

One of the real beauties of this approach is that it is possible to provide insightful, customized reports to each manager and offer specific recommendations for actions the manager should take — based on his or her specific pattern of results — to help that manager achieve his or her objectives.

Once this has been achieved, it is typically no longer necessary for HR to push the findings of the employee engagement survey onto the organization — the organization starts to pull for the analysis and insights. The move from push to pull is a significant breakthrough in HR’s ability to help the organization be truly strategic.

There are powerful forces — in terms of both supply and demand — that are bringing HR analytics to the forefront. First, technology advances have made HR data available on a scale that was heretofore unimaginable. More importantly, the growing economic premium associated with superior human capital management means that HR strategy is simply too important to be left to gut and intuition. If HR doesn’t step up to the plate, another part of the organization is sure to fill the void.

Laurie Bassi is CEO of McBassi & Co. and chairman of Bassi Investments. Dan McMurrer is chief analyst at McBassi & Co. and chief research officer at Bassi Investments. They are co-authors of Good Company: Business Success in the Worthiness Era. They can be reached at editor@talentmgt.com.

Read MoreWithout some essential ingredients, surveys provide no real value to support goals. To find out what these ingredients are, click here.